Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
http://ai.googleblog.com/2021/02/evaluating-design-trade-offs-in-visual.html
@Machin_learn
http://ai.googleblog.com/2021/02/evaluating-design-trade-offs-in-visual.html
@Machin_learn
research.google
Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
Posted by Mohammad Babaeizadeh, Research Engineer and Dumitru Erhan, Research Scientist, Google Research Model-free reinforcement learning has been...
2006.02493.pdf
2.4 MB
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE #paper @Machine_learn
feature enginnering for machine learning.pdf
3.9 MB
Feature Engineering for Machine Learning
Principles and Techniques for Data Scientists
#book
@Machine_learn
Principles and Techniques for Data Scientists
#book
@Machine_learn
WeNet open source, production first and production ready end-to-end (E2E) speech recognition toolkit
Github: https://github.com/mobvoi/wenet
Paper: https://arxiv.org/abs/2102.01547v1
Tutorial: https://github.com/mobvoi/wenet/blob/main/docs/tutorial.md
@Machine_learn
Github: https://github.com/mobvoi/wenet
Paper: https://arxiv.org/abs/2102.01547v1
Tutorial: https://github.com/mobvoi/wenet/blob/main/docs/tutorial.md
@Machine_learn
Machine Learning for Computer Architecture
http://ai.googleblog.com/2021/02/machine-learning-for-computer.html
@Machine_learn
http://ai.googleblog.com/2021/02/machine-learning-for-computer.html
@Machine_learn
research.google
Machine Learning for Computer Architecture
Posted by Amir Yazdanbakhsh, Research Scientist, Google Research One of the key contributors to recent machine learning (ML) advancements is the de...
TracIn — A Simple Method to Estimate Training Data Influence
http://ai.googleblog.com/2021/02/tracin-simple-method-to-estimate.html
@Machine_learn
http://ai.googleblog.com/2021/02/tracin-simple-method-to-estimate.html
@Machine_learn
research.google
TracIn — A Simple Method to Estimate Training Data Influence
Posted by Frederick Liu and Garima Pruthi, Software Engineers, Google Research The quality of a machine learning (ML) model’s training data can hav...
Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
http://ai.googleblog.com/2021/02/evaluating-design-trade-offs-in-visual.html
@Machine_learn
http://ai.googleblog.com/2021/02/evaluating-design-trade-offs-in-visual.html
@Machine_learn
research.google
Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning
Posted by Mohammad Babaeizadeh, Research Engineer and Dumitru Erhan, Research Scientist, Google Research Model-free reinforcement learning has been...
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Building Image Segmentation Faster Using Jupyter Notebooks from NGC
https://developer.nvidia.com/blog/building-image-segmentation-faster-using-jupyter-notebooks-from-ngc/
@Machine_learn
https://developer.nvidia.com/blog/building-image-segmentation-faster-using-jupyter-notebooks-from-ngc/
@Machine_learn
Neural-Backed Decision Trees
Demo: https://research.alvinwan.com/neural-backed-decision-trees/
Github: https://github.com/alvinwan/neural-backed-decision-trees
Paper: https://arxiv.org/abs/2004.00221
Code: https://colab.research.google.com/github/alvinwan/neural-backed-decision-trees/blob/master/examples/load_pretrained_nbdts.ipynb
Dataset: https://pytorch.org/docs/stable/torchvision/datasets.html
@Machine_learn
Demo: https://research.alvinwan.com/neural-backed-decision-trees/
Github: https://github.com/alvinwan/neural-backed-decision-trees
Paper: https://arxiv.org/abs/2004.00221
Code: https://colab.research.google.com/github/alvinwan/neural-backed-decision-trees/blob/master/examples/load_pretrained_nbdts.ipynb
Dataset: https://pytorch.org/docs/stable/torchvision/datasets.html
@Machine_learn
How to Speed up Scikit-Learn Model Training
https://www.kdnuggets.com/2021/02/speed-up-scikit-learn-model-training.html
@Machine_learn
https://www.kdnuggets.com/2021/02/speed-up-scikit-learn-model-training.html
@Machine_learn
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🧪 Alchemy: A structured task distribution for meta-reinforcement learning
Deepmind: https://deepmind.com/research/publications/alchemy
Github: https://github.com/deepmind/dm_alchemy
Paper: https://arxiv.org/abs/2102.02926
@Machine_learn
Deepmind: https://deepmind.com/research/publications/alchemy
Github: https://github.com/deepmind/dm_alchemy
Paper: https://arxiv.org/abs/2102.02926
@Machine_learn
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software
Github: https://github.com/EdisonLeeeee/GraphGallery
Paper: https://arxiv.org/abs/2102.07933v1
@Machine_learn
Github: https://github.com/EdisonLeeeee/GraphGallery
Paper: https://arxiv.org/abs/2102.07933v1
@Machine_learn
Introducing Model Search: An Open Source Platform for Finding Optimal ML Models
http://ai.googleblog.com/2021/02/introducing-model-search-open-source.html
@Machine_learn
http://ai.googleblog.com/2021/02/introducing-model-search-open-source.html
@Machine_learn
research.google
Introducing Model Search: An Open Source Platform for Finding Optimal ML Models
Posted by Hanna Mazzawi, Research Engineer and Xavi Gonzalvo, Research Scientist, Google Research The success of a neural network (NN) often depend...